Fuzzy Differential Equations
Wen Yu, Raheleh Jafari · 2019
This chapter presents a review of the methodologies associated with the modeling and control of uncertain nonlinear systems. The basic criteria that highlight the work rely on the various patterns of techniques incorporated into the solutions of fuzzy differential equations (FDEs) that correspond to the controllability constraint related to fuzzy control. The application of the FDEs is in direct connection with the nonlinear modeling and control. Fuzzy control with FDEs requires the solution of the FDEs. The chapter also presents several approaches such as the predictor–corrector method, the Adomian decomposition method, the Euler method, the Taylor method, the Runge–Kutta method, The finite difference method, the differential transform method, and the neural network method. Taking into consideration the modeling case as well as the control of uncertain nonlinear systems, the implementation of a neural networks technique has contributed to the complex method of dealing with the appropriate coefficients and solutions of fuzzy systems.